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Data Label Jobs in Ohio (NOW HIRING)

Accenture

Data Protection Sr. Analyst

Cleveland, OH · Hybrid

$84K - $100K/yr

Basic understanding of data classification/labeling, DLP policies and rules, and regulatory concepts (e.g., GDPR, HIPAA - awareness level). * PowerShell scripting or automation exposure is a plus.

Accenture

Data Protection Sr. Analyst

Columbus, OH · Hybrid

$84K - $100K/yr

Basic understanding of data classification/labeling, DLP policies and rules, and regulatory concepts (e.g., GDPR, HIPAA - awareness level). * PowerShell scripting or automation exposure is a plus.

Accenture

Data Protection Sr. Analyst

Cincinnati, OH · Hybrid

$84K - $100K/yr

Basic understanding of data classification/labeling, DLP policies and rules, and regulatory concepts (e.g., GDPR, HIPAA - awareness level). * PowerShell scripting or automation exposure is a plus.

Deloitte

Manager

Morristown, OH

Experience with artificial intelligence (AI) and generative AI data readiness, including data scoping, bias detection, data labeling, and regulated or ethical AI considerations * Experience ...

Accenture

Data Protection Manager

Columbus, OH · On-site +1

$150K - $178K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

Accenture

Data Protection Manager

Cleveland, OH · On-site +1

$150K - $178K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

Accenture

Data Protection Manager

Cincinnati, OH · On-site +1

$150K - $178K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

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Data Label information

What is the difference between Data Label vs Data Annotator?

AspectData LabelData Annotator
Primary RoleAssigns labels to data for machine learning modelsPerforms detailed annotation of data, including labeling and marking specific features
Skills & CertificationsBasic understanding of data types, labeling toolsMore detailed annotation skills, familiarity with annotation tools
Work EnvironmentData labeling platforms, remote or on-siteAnnotation tools, often similar to labeling platforms
Industry UsageUsed across AI, machine learning, and data science projectsUsed in similar fields, often with more complex annotation tasks

Data Label and Data Annotator roles are closely related, with Data Labeling focusing on assigning simple labels to data, while Data Annotators perform more detailed and complex annotations. Both roles are essential in preparing data for AI and machine learning, often using similar tools and working within the same industry environments.

What are some common challenges faced by Data Labelers, and how can they be addressed?

Data Labelers often face challenges such as handling large volumes of repetitive data, maintaining high accuracy under tight deadlines, and quickly adapting to changing labeling guidelines. To address these challenges, it's important to develop strong attention to detail, use quality control processes like regular peer reviews, and communicate proactively with team leads if guidelines are unclear. Additionally, many teams use specialized annotation tools to streamline workflows and minimize errors, making it helpful to become familiar with these platforms.

What are the key skills and qualifications needed to thrive as a Data Labeler, and why are they important?

To thrive as a Data Labeler, you need strong attention to detail, basic computer literacy, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Experience with labeling platforms, annotation tools, and sometimes knowledge of data management systems is typically required. Reliability, consistency, and the ability to follow precise instructions are the soft skills that set top performers apart. These skills ensure accurate and high-quality data labeling, which is critical for training effective machine learning models.

What are data labelers?

Data labelers are professionals who annotate or tag data—such as images, text, or audio—to provide context and structure for use in machine learning and artificial intelligence projects. Their work involves identifying and labeling key features in raw data so that algorithms can learn to recognize patterns and make predictions. Data labeling is a crucial step in training supervised learning models, ensuring the accuracy and effectiveness of AI systems.
What are popular job titles related to Data Label jobs in Ohio? For Data Label jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Label jobs in Ohio look for? The top searched job categories for Data Label jobs in Ohio are:
What cities in Ohio are hiring for Data Label jobs? Cities in Ohio with the most Data Label job openings:
Data Label jobs near you
Infographic showing various Data Label job openings in Ohio as of May 2026, with employment types broken down into 2% Internship, 7% As Needed, 65% Full Time, 22% Part Time, 2% Contract, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.
Ergon Asphalt and Emulsions - Data Analysts I (2)

Ergon Asphalt and Emulsions - Data Analysts I (2)

Ergon

Heath, OH • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Ergon Inc. rating

8.0

Company rating: 8.0 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

22nd of 74 rated oil and gas companies

Job description

We are a great company with great pay and great benefits. Ergon, Inc. is a relationship-driven company that values each employee's willingness to learn and contribute to the team. We are family owned with locations throughout the world, but we pride ourselves on maintaining a small-company feel.

Position Summary

The Data Analyst I is responsible for supporting the development, management, and validation of accurate roadway inventory and condition data across all client projects. This entry-level role plays a key part in transforming raw data into structured, reliable information that supports Pavement Condition Index (PCI) calculations, reporting, and final deliverables.

Working under general supervision, the Data Analyst I assists in ensuring data integrity, supporting condition assessments, and contributing to quality assurance processes. This role also supports ongoing improvements to roadway analysis tools.

Key Responsibilities

Data Management & Processing

  • Collect, organize, and process roadway inventory and condition data from multiple sources
  • Validate data accuracy and completeness in alignment with ASTM standards
  • Perform routine data remediation tasks, including identifying inconsistencies, correcting errors, and standardizing datasets
  • Maintain organized and traceable datasets to support downstream analysis and reporting

Analysis & Reporting Support

  • Assist in preparing datasets for PCI calculations and project deliverables
  • Perform basic data analysis to identify trends, anomalies, and data gaps
  • Support the generation of client-ready outputs by ensuring consistency and accuracy of data

AI Data Validation & Support

  • Review roadway distress outputs
  • Validate distress types, severity levels, and quantities against established standards
  • Provide feedback on outputs to support continuous improvement and model refinement
  • Assist in bridging automated data processing with human quality validation

Quality Assurance & Standards Compliance

  • Support QA/QC processes by reviewing datasets for adherence to quality standards
  • Ensure consistency across data systems and project deliverables
  • Participate in maintaining and improving data standards and documentation

Collaboration & Process Improvement

  • Work closely with GIS, QA/QC, and operations teams to ensure seamless data integration
  • Support cross-functional efforts to deliver projects on time and within quality expectations
  • Contribute to workflow efficiencies, process improvements, and scalability initiatives

Qualifications

Education

  • Associate's degree (or in pursuit of) in Data Analytics, Engineering, GIS, Computer Science, Statistics, or a related field (or equivalent experience)

Experience

  • 0–2 years of experience in data analysis, data processing, or a related field
  • Exposure to infrastructure, roadway, or asset management data preferred but not required

Technical Skills

  • Basic proficiency in data analysis tools (e.g., Excel, SQL, or similar)
  • Familiarity with GIS concepts or tools (e.g., ArcGIS, QGIS) is a plus
  • Ability to work with large datasets and perform data validation
  • Exposure to AI/ML concepts or data labeling/validation is beneficial

Core Competencies

  • Strong attention to detail and commitment to data accuracy
  • Analytical thinking and problem-solving skills
  • Ability to follow defined processes and standards
  • Effective communication and teamwork skills
  • Willingness to learn and adapt in a technology-driven environment

Working Conditions

  • Primarily office-based or remote work with extended periods of computer use
  • May require occasional coordination across teams or departments to meet project deadlines

Come join the team!

Must be able to pass a pre-employment drug screen and background check. A clean MVR is required.

We are an EEO/AAP employer.

Job Role: Data Analyst I

Location: Heath, OH

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